Your browser does not support JavaScript!

Antenna array design using EAs

Antenna array design using EAs

For access to this article, please select a purchase option:

Buy chapter PDF
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Emerging Evolutionary Algorithms for Antennas and Wireless Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This chapter presents several antenna array design cases by using different evolution-ary algorithms (EAs) and comparing results. The synthesis of antenna arrays plays a very important role in communication systems. Array synthesis is a classic and challenging optimization problem, which has been extensively studied using several analytical or stochastic methods. The increased use of such arrays creates more challenges upon the antenna engineers. More requirements, such as pattern shaping, low profile, wideband/narrowband, and interference cancellation; and more limitations such as power dissipation and antenna size, lead to the urgent need for simple, time saving, and efficient optimization tech-niques. Common optimization goals in array synthesis are the sidelobe level (SLL) suppression and the matching of the mainlobe to a desired pattern. Thus, the opti-mization problem is usually to find a set of element excitations and/or positions that closely match a desired pattern. The desired pattern shape can vary widely depending on the application. Several new synthesis and optimization techniques have emerged in the last two decades that mimic biological evolution, brain function, or the way biological entities communicate in nature. Several of these methods have been applied to the array design problem

Chapter Contents:

  • 3.1 Linear-array design
  • 3.1.1 Position-only optimization
  • 3.1.2 Phase-only optimization
  • 3.1.3 Position and phase optimization
  • 3.1.4 Amplitude-only optimization
  • 3.2 Thinned-array design
  • 3.3 Shaped beam synthesis
  • 3.4 Planar thinned-array design
  • 3.5 Conformal array design
  • 3.6 Reducing the number of elements in array design
  • 3.6.1 20-Element Chebyshev array
  • 3.6.2 A 29-element Taylor–Kaiser array
  • References

Inspec keywords: interference suppression; antenna arrays; stochastic programming

Other keywords: biological entities; efficient optimization techniques; array synthesis; antenna size; antenna array design; power dissipation; optimization problem; sidelobe level; mimic biological evolution; interference cancellation; element excitations; analytical method; stochastic method; antenna engineers; communication systems

Subjects: Electromagnetic compatibility and interference; Optimisation techniques; Optimisation techniques; Antenna arrays

Preview this chapter:
Zoom in

Antenna array design using EAs, Page 1 of 2

| /docserver/preview/fulltext/books/ew/sbew534e/SBEW534E_ch3-1.gif /docserver/preview/fulltext/books/ew/sbew534e/SBEW534E_ch3-2.gif

Related content

This is a required field
Please enter a valid email address